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Dr. Anmol Agarwal: AI and Machine Learning in Cybersecurity

Dr. Anmol Agarwal: AI and Machine Learning in Cybersecurity

Released Tuesday, 14th May 2024
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Dr. Anmol Agarwal: AI and Machine Learning in Cybersecurity

Dr. Anmol Agarwal: AI and Machine Learning in Cybersecurity

Dr. Anmol Agarwal: AI and Machine Learning in Cybersecurity

Dr. Anmol Agarwal: AI and Machine Learning in Cybersecurity

Tuesday, 14th May 2024
Good episode? Give it some love!
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About the Guest:Dr. Anmol Agarwal is a senior security researcher focused on securing 5G and 6G. Her research interests include AI and Machine Learning security. She is also an adjunct professor teaching Machine Learning to doctoral students. She holds a doctoral degree in cybersecurity analytics and previously worked at the U.S. Cybersecurity and Infrastructure Security Agency managing risk to the federal enterprise. Dr. Agarwal is also an active speaker and has spoken at numerous events and conferences to educate the public about cybersecurity and data science concepts. In her free time, she enjoys mentoring others in the community, traveling, and spending time with her family.

Episode Summary:In this intriguing episode of the Phillip Wylie Show, we delve into the rapidly evolving intersection of AI and cybersecurity with Dr. Anmol Agarwal. Phillip and Dr. Agarwal engage in a comprehensive discussion that illuminates the cutting-edge advancements in telecommunications security, the ethical considerations of AI, and practical advice for those looking to break into the cybersecurity field.Dr. Agarwal shares her journey from computer science student to an authoritative voice in the AI and cybersecurity realm, revealing insights into the quarterly meetings for 5G and 6G standardization. She provides valuable knowledge on how both offensive and defensive strategies are shaping AI utilization in security and offers resource recommendations for those aspiring to pen-test AI and machine learning systems. The conversation uncovers the current and potential applications of AI in various technologies and initiatives, from digital twins to deepfakes, and how they pose significant opportunities and threats to cybersecurity.

Key Takeaways:

  • AI and cybersecurity are intertwined fields that benefit from understanding both the cybersecurity fundamentals and AI technologies.
  • OWASP offers resources regarding AI vulnerabilities, and Mitre Atlas provides a matrix on AI attacks for those interested in pen-testing AI.
  • Digital twins and AI-generated content such as deepfakes are emerging technologies that both excite and concern cybersecurity professionals, emphasizing the need for advanced security measures.
  • A career in cybersecurity remains promising due to the continuous emergence of new technologies that will invariably require secure implementation and management.
  • Free online platforms like Kaggle and Sklearn tutorials are recommended for learning machine learning and Python for AI applications.

    Notable Quotes:

  • "I actually got enlightened into cybersecurity, and I realized I like cybersecurity because we had so many college clubs." - Anmol Agarwal
  • "I don't think you need to code to be in cybersecurity… But there are so many career paths in cybersecurity that don't require any coding." - Anmol Agarwal
  • "Now we're seeing AI is starting to create deepfakes that are more realistic looking." - Anmol Agarwal
  • "Whenever a new technology comes out or there's a disruptive startup, we need security to actually secure this technology." - Anmol Agarwal
  • "AI is going to allow us to prevent or detect certain kinds of attacks that might occur in the system." - Anmol Agarwal

    Resources:

  • https://www.linkedin.com/in/anmolsagarwal/
  • https://twitter.com/anmolspeaker
  • OWASP Top Ten for Large Language Models: https://owasp.org/www-project-top-10-for-large-language-model-applications/
  • MITRE Atlas Framework: https://atlas.mitre.org
  • Kaggle Online Learning Platform: https://www.kaggle.com
  • Gandalf - https://gandalf.lakera.ai/
  • SK learn Python Package: SK learn Documentation https://scikit-learn.org


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